Locating features within an image is fundamental to computer vision applications. The edges (or outline) of objects within the image are frequently the most useful features since the edges typically provide object shape information. The shape information facilitates subsequent object acquisition or recognition processing. The rapid increase in microprocessor throughput capabilities in recent years has fueled proliferation of computer vision applications in many diverse fields. Examples include automated processing of images in medical diagnostics, reconnaissance, missile guidance, hazard or threat warning systems, security systems, access control systems (e.g. face recognition), navigation, geographic mapping, manufacturing quality inspection, robot vision, search and rescue, etc.
One problem with conventional image processing systems is that the methods employed for edge detection and generation of edge images are not very tolerant to noise. Another problem with convention image processing systems is that significant throughput time is required for improved noise tolerance. Another problem with convention edge detection systems is that conventional methods may not achieve optimal edge filtering along arbitrary paths.
Thus, there is a general need for an improved image processing system and method. Thus, there is also a need for improved systems and methods for edge detection and generation of edge images. There is also a need for an improved edge detection and edge image generation system and method that provides improved noise tolerance and lowers the cost of imaging equipment greatly improving the affordability of an image processing system. Thus, there is also a need for an improved edge detection and edge image generation system and method with improved noise tolerance without significant throughput increases. Thus there is also a need for an edge detection system that may automatically adjust to any edge orientation or shape rather than being constrained to a discrete set of straight edge orientations to help achieve optimal edge filtering along arbitrary paths.